Robinhood Chain tokenized-stock perp open interest & stats on Lighter: open interest (base + USD notional), mark/index/last price, 24h volume, price change, and daily high/low/trades. Send { ticker }. Positioning and liquidity depth for tokenized-equity perp traders. [x402 paid tool — price $0.05; POST /api/rh/perp-oi]
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Stock/ETF ticker, e.g. TSLA |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that it is a paid tool costing $0.05 and uses POST /api/rh/perp-oi. This goes beyond typical read-only description, though it does not mention authentication or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is densely packed with useful information including data fields, pricing, and endpoint. It is front-loaded with the main purpose but could be slightly more concise without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description thoroughly lists the return values (open interest, prices, volume, etc.) and mentions positioning and liquidity depth. For a single-parameter tool, it provides complete context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for ticker. The description only adds 'Send { ticker }' which adds no additional meaning, so it meets the baseline but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides open interest and stats for Robinhood Chain tokenized-stock perps, listing specific data fields. It distinguishes from sibling tools by focusing on perp open interest and stats for tokenized-equity perps, which is unique among the listed siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for tokenized-equity perp traders but does not explicitly state when to use this tool versus alternatives like perps_oi or rh_perp_funding. No when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are organized by domain prefix (e.g., 'crypto_', 'rh_', 'snipe_'), which helps distinguish between areas. Within each domain, they serve distinct purposes, though some overlap between domains exists (e.g., price data appears in multiple groups). Overall, an agent can navigate effectively.
All tool names follow a consistent snake_case pattern with a domain prefix and a verb_noun combination (e.g., 'compliance_risk', 'rh_stock', 'snipe_honeypot'). This makes the API predictable and easy to explore.
With 159 tools, the server is extremely large. While the broad scope of web3 and utility functions justifies many tools, the count is significantly above the typical range for a coherent toolkit, potentially overwhelming agents and increasing selection error.
The toolkit covers a wide range of web3 operations: crypto, DeFi, compliance, safety, scheduling, memory, etc. There are no obvious major gaps for its intended purpose, though some niche areas might be missing.